Method and apparatus for performing different decoding algorithms in different locations

ABSTRACT

A method and apparatus for decoding codes applied to objects for use with an image sensor that includes a two dimensional field of view (FOV), the method comprising the steps of providing a processor programmed to perform the steps of obtaining an image of the FOV and applying different decode algorithms to code candidates in the obtained image to attempt to decode the code candidates wherein the decode algorithm applied to each candidate is a function of the location of the code candidate in the FOV.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 15/905,049 filed Feb. 26, 2018, which is acontinuation of U.S. patent application Ser. No. 15/148,305 filed May 6,2016, now U.S. Pat. No. 9,904,833, which is a division of U.S. patentapplication Ser. No. 13/288,098 filed Nov. 3, 2011, now U.S. Pat. No.9,367,725 issued Jun. 14, 2016, all of which are incorporated herein byreference in their entirety for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

BACKGROUND OF THE INVENTION

The present invention relates to code readers and more specifically tocode readers that attempt to optimize decode processes to expediteanalysis of code candidates in obtained images.

Automated identification of products using optical codes has beenbroadly implemented throughout industrial operations and in many otherapplications for many years. Optical codes are patterns composed ofelements with different light reflectance or emission, assembled inaccordance with predefined rules. The elements in the optical codes maybe bars or spaces in a linear barcode, or the on/off pattern in atwo-dimensional matrix code. The bar code or symbols can be printed onlabels placed on product packaging, or directly on the product itself bydirect part marking. The information encoded in a bar code or symbol canbe decoded using optical readers in fixed-mount installations or inportable hand held devices. In the case of a hand held reader device, adevice user directs the device toward a code often with the aid of alight target pattern generated by the device which appears on an objectsurface to be imaged and the device either automatically obtains imagesincluding the code or the user activates the device to obtain images.

At least some reader devices include a camera capable of generating twodimensional images of a field of view. For example, many systemscurrently employ a two dimensional CCD image sensor which obtains imagesand generates image data which is provided to a processor. The processoris programmed to examine image data to identify code candidates (e.g.,bar code or symbol candidates) and attempt to decode the codecandidates. At least some reader devices are programmed to obtain imagesof a FOV in rapid succession and to attempt to decode any codecandidates in the obtained images as quickly as possible. To decodecodes, the processor runs one or more decode algorithms.

When obtaining an image of a code, the quality of the image depends onseveral factors including the angle of a sensor with respect to asurface on which the code is applied, the material and texture of thesurface on which the code is applied, code marking quality or damageafter marking, ambient and device lighting characteristics, distancefrom the surface on which the code is applied, optical blur, cameraresolution, etc. Image quality affects the ability of a processorrunning a specific algorithm to decode a code. For example, in manycases a simple decoding algorithm will not be able to successfullydecode codes in an image unless the circumstances surrounding imageacquisition are substantially ideal.

To compensate for imperfect image acquisition, relatively more complexdecode algorithms have been developed. For instance, several decodealgorithms have been developed which can at least partially compensatefor imperfect lighting, a curved surface that a code is applied to,imperfect sensor angle with respect to the surface that a code isapplied to, etc.

While complex decode algorithms work well to compensate for imperfectimages, one draw back is that complex algorithms often require a greateramount of processing power and a commensurate amount of time to perform.Hereinafter, unless indicated otherwise, algorithms that are relativelycomplex or more generally algorithms that require a relatively longperiod to perform will be referred to as “expensive” or “more expensive”algorithms while algorithms that are relatively simple or more generallythat require a relatively short period to complete will be referred toas “inexpensive” or “less expensive” algorithms.

While more expensive algorithms are not an issue in some applications,in applications where images are obtained in rapid succession, expensivealgorithms requiring relatively long periods to complete can result incomputational requirements that far exceed capabilities of readerprocessors. More specifically, in some cases, image sensors are capableof obtaining and providing images so quickly that a reader deviceprocessor cannot perform an expensive algorithm on all code candidatesin an image prior to receiving a next image.

Where a processor cannot keep up with the computational demands requiredto perform an expensive algorithm for all code candidates in a rapidsuccession of images, one solution may be to forego analysis ofcandidates in next images until a reader device has attempted to decodeall code candidates in a current image. Thus, for instance, where secondthrough fourth images are obtained during the period required to attemptto decode all code candidates in a first image, the second throughfourth images would be discarded when a fifth image is obtained and codecandidates in the fifth image would be examined. While this solutionensures that the expensive algorithm is applied to all code candidatesin a current or first image, this solution simply ignores codecandidates in the second through fourth image while candidates in thefirst image are processed despite the fact that candidates in thesubsequent images may be better suited to be decoded. In this case, theoverall time required to successfully image and decode a code will beprolonged where the device is unable to successfully decode anycandidate in the first image which can result in a bothersome delay fora device user.

BRIEF SUMMARY OF THE INVENTION

Consistent with at least one aspect of some embodiments of theinvention, it has been recognized that decode algorithms that havedifferent relative expenses (i.e., that require different amounts oftime to complete) can be used to analyze obtained images in order toexpedite the overall decoding process to the point where a processor mayattempt to identify all of at least a subset of code candidates in animage and to decode all of the candidates in the subset using at leastsome algorithm. More specifically, which algorithms to apply to portionsof an image to identify candidates and which algorithms to apply tospecific code candidates in an image can be advantageously determined bylocation within the image.

For instance, in the case of a hand held reader device where a deviceuser manually moves the reader device during use to align the reader'sfield of view (FOV) with a code to be read, most users continually movea reader device to better align the code with the FOV and to betterposition the reader with respect to the surface that the code is appliedto until the device indicates that the code has been successfullydecoded (e.g., a light is illuminated, a sound is generated, data isreturned on a communication channel, etc.). Thus, at the beginning of amanual alignment process and when first images including a code areobtained, the code may be located near the outside edge of a FOV and thecamera may be angled with respect to the surface on which the code hasbeen applied. Through manual adjustments and during subsequent imaging,the code will be more aligned with the central portion of the FOV andthe camera to surface angle will likely be more optimal. In this case,in at least some embodiments, it makes sense to divide the FOV into acentral region of interest (ROI) and a peripheral ROI and to attempt toidentify code candidates in and decode code candidates in the centralROI using a more expensive algorithm while attempting to identify codecandidates in and decode candidates in the peripheral ROI using a lessexpensive decode algorithm. Thus, in a first image obtained when a FOVis imperfectly aligned with a code, the code may be located in theperipheral ROI and in that case only less expensive algorithms would beapplied to identify the code candidate and decode the code. In asubsequent image that includes the code in the central ROI, moreexpensive algorithms would be applied to identify the code candidate anddecode the candidate code.

Here, in many cases, the less expensive algorithm will successfullydecode a code candidate in a first or early image, the device willindicate a successful decode and the process will be completed. In othercases, when the first or early images are examined, neither of thealgorithms will be able to successfully decode a code. However, here, insubsequent images, the code candidate associated with the code willreflect a more optimal FOV-to-code alignment and therefore the expensivealgorithm will be able to be completed relatively faster and the overalldecoding process should be shortened on average.

In other cases the FOV may be divided into three or more ROIs anddifferent decode algorithms may be applied to the candidates in each ofthe three or more ROIs.

While the ROIs may be pre-specified based on an assumed manner in whicha reader device will be employed, in other embodiments the ROIs may bealtered essentially in real time to reflect the way in which a device isbeing employed. For instance, in some cases an “expensive ROI”, meaningan ROI in which a processor attempts to locate and decode candidatesusing a more expensive decode algorithm, may be assigned to a region ofa FOV in which a previous code was last successfully decoded. Thus,where the most recently decoded code was located near a left side of aFOV, the expensive ROI may be moved to that location where the balanceof the FOV would include a less expensive ROI.

In some embodiments ROIs may be altered essentially in real time tochange their relative size based on how fast a device is completing allrequired candidate decode attempts for an image. For instance, a centralexpensive ROI may be increased in size if a processor completes alldecode attempts for one or a series of images prior to or with at leasta threshold period prior to the processor receiving a next image fromcamera similarly, the expensive ROI may be decreased in size if aprocessor is unable to attempt to decode all image candidates in arequired period. By increasing the size of the central expensive ROI,more code candidates should appear in the central ROI for decodeattempts in subsequent images thereby increasing the time required tocomplete all of the decode attempts for an image.

In some embodiments the locations of code candidates may be used inother ways to determine which algorithms to apply to which codes. Forinstance, it may be that for a specific expensive algorithm it is knownthat a processor will always be able to attempt to decode threecandidates prior to the processor receiving a next image. Here, theprocessor may be programmed to select the three most centrally locatedcode candidates for decode attempts using the expensive algorithm andmay attempt to decode all other candidates using a less expensivealgorithm.

In still other embodiments a reader device processor may be programmedto start at a point of interest within an image, order code candidatesin an order where closest candidates to the point of interest are firstand candidates further from the point are listed subsequently and tothen attempt to decode code candidates in that order until some nextimage event occurs. Here, the next image event may be reception of anext image from a camera. In other cases the next image event may betriggered by expiration of a timer which times out a period which shouldexpire prior to reception of a next image. Other next image events arecontemplated.

Consistent with another aspect of at least some embodiments of thepresent invention, a reader device processor may be programmed to applya first relatively inexpensive decode algorithm to code candidates in aseries of images and if the device processor fails to successfullydecode a code in any of the images, may store those images in a memory.Thereafter, the processor may be programmed to, after a set of imageshave been stored, re-access one or a sub-set or all of the images andapply a more expensive decode algorithm to all or a subset of the codecandidates in the image or images to attempt to decode the candidates.In at least some cases when the image or images are re-accessed, themore expensive algorithm may be applied in a manner consistent with anyof the above teachings such as, for instance, by applying the expensivealgorithm to an ROI of the image or images that is smaller than the FOV,by applying the expensive algorithm to only a subset of the candidates(e.g., 3) in the image or in each image that are closest to a point ofinterest, etc. In some cases, when the processor re-accesses more thanone image, the processor may start processing the most recently storedimage first and work back toward the earlier stored images, as alignmentor positioning of the FOV and code in at least some applications (e.g.,hand held applications) should be better in the subsequent images. Otherorders for processing the stored images are contemplated.

In still other embodiments when a processor is unsuccessful in decodingcode candidates in an image, prior to storing the image for subsequentprocessing, the processor may assign a decode success factor to theimage which can be used by the processor to identify a subset of thestored images that the processor should analyze using the expensivealgorithm.

In still other embodiments the processor may be programmed to attempt todecode all code candidates using an inexpensive algorithm and, when allattempts fail, to attempt to decode only a subset of the candidatesbased on location as indicated in any of the examples above. In thealternative, the processor may be programmed to assign a decode successfactor to at least a subset (e.g., 3-5) of the code candidates that,based on the less expensive decode attempts, have the highest likelihoodof being successfully decoded using the expensive algorithm and may thenapply the expensive algorithm to the candidate subset.

Moreover, in at least some cases, when the processor re-accesses a codecandidate that the processor attempted to decode previously using a lessexpensive algorithm, the processor may use information generated whenthe less expensive algorithm was applied to expedite the process forcompleting the more expensive algorithm. For instance, where theprocessor was able to analyze three fourths of a code using the lessexpensive algorithm, that information may be used to expedite thesubsequent algorithm.

Some embodiments include a method for decoding codes applied to objectsfor use with an image sensor that includes a two dimensional field ofview (FOV), the method comprising the steps of providing a processorprogrammed to perform the steps of, obtaining an image of the FOV,identifying at least first and second regions of interest (ROIs) in theimage wherein the first ROI is different than the second ROI, attemptingto decode code candidates in the first ROI using a first decodealgorithm and attempting to decode code candidates in the second ROIusing a second decode algorithm that is different than the first decodealgorithm.

In some cases the first decode algorithm is computationally more complexthan the second decode algorithm. In some cases the first decodealgorithm requires a greater amount of time to complete than the seconddecode algorithm. In some cases the first ROI includes a central portionof the FOV. In some cases the second ROI includes portions of the FOVsurrounding the first ROI. In some cases the first decode algorithmincludes the second decode algorithm and an additional decode algorithm.In some cases the first ROI includes an ROI corresponding to thelocation of a successfully decoded code in a prior image.

In some cases the method further includes the steps of identifying atleast a third ROI in the image which is different than the first andsecond ROIs and attempting to decode code candidates in the third ROIusing a third decode algorithm that is different than the first andsecond decode algorithms. In some embodiments the method furtherincludes the steps of receiving an indication from an individualindicating the first ROI or optimal location. In some cases the firstROI includes a position within the FOV and a distance relative to theposition. In some cases the position consists of a location along asingle axis within the image. In some cases the image sensor forms partof a portable code reading device. In some cases the image sensor formspart of a hand held code reading device.

In some embodiments the sensor obtains images in a repetitive fashionand wherein the size of the first ROI is determined at least in part asa function of the time required to attempt to decode code candidates inthe first ROI in a prior obtained image. In some cases the sensorobtains images in a repetitive fashion and wherein the second decodealgorithm is selected at least in part as a function of the timerequired to attempt to decode code candidates in a prior obtained image.In some cases the first and second ROIs are prespecified prior toobtaining the image.

Some embodiments include a method for decoding codes applied to objectsfor use with an image sensor that includes a two dimensional field ofview (FOV), the method comprising the steps of providing a processorprogrammed to perform the steps of, obtaining an image of the FOV andapplying different decode algorithms to code candidates to attempt todecode the code candidates wherein the decode algorithm applied to eachcandidate is a function of the location of the code candidate in theFOV.

In some cases a first decode algorithm is applied to code candidateswithin a first region of interest (ROI) and a second decode algorithmthat is different than the first decode algorithm is applied to codecandidates in a second ROI that is different than the first ROI. In somecases the first ROI includes a central portion of the sensor FOV and thesecond ROI includes portions of the FOV that surround the first ROI. Insome cases the sensor forms part of a hand held device. In some casesthe function that determines which decode algorithms are applied towhich code candidates changes to optimize the decode process.

In some cases the decode algorithms include at least a first relativelycomplex decode algorithm and a second relative simple decode algorithmand wherein the function changes to alter the ratio of code candidatesto which the first and second decode algorithms are applied. In somecases the ratio is altered as a function of the time required to attemptto decode code candidates in the FOV using the first and second decodealgorithms.

Still other embodiments include a method for decoding codes applied toobjects for use with an image sensor that includes a two dimensionalfield of view (FOV), the method comprising the steps of providing aprocessor programmed to perform the steps of, (i) obtaining an image ofthe FOV, (ii) attempting to decode a the code candidate in the imageusing a first decode algorithm, (iii) where the attempt to decode thecode candidate fails, maintaining the image in memory, (iv) repeatingsteps (i) through (iii) until one of a threshold number of attempts todecode the code candidate have failed and the code candidate has beensuccessfully decoded, when the threshold number of attempts to decodethe code candidate have failed, accessing the images maintained inmemory and attempting to decode the code candidate in at least a subsetof the images stored in memory using a second decoding algorithm that isdifferent than the first decoding algorithm.

Other embodiments include an apparatus for reading codes applied toobjects, the apparatus comprising image sensor that includes a twodimensional field of view (FOV), a processor linkable to the sensor toobtain image data there from, the processor programmed to perform thesteps of, obtaining an image of the FOV, identifying at least first andsecond regions of interest (ROIs) in the image wherein the first ROI isdifferent than the second ROI, attempting to decode code candidates inthe first ROI using a first decode algorithm and attempting to decodecode candidates in the second ROI using a second decode algorithm thatis different than the first decode algorithm.

In some cases the first decode algorithm is computationally more complexthan the second decode algorithm. In some cases the first decodealgorithm requires a greater amount of time to complete than the seconddecode algorithm. In some cases the first ROI includes a central portionof the FOV.

Yet other embodiments include an apparatus for decoding codes applied toobjects for use with an image sensor that includes a two dimensionalfield of view (FOV), the apparatus comprising an image sensor includinga two dimensional field of view (FOV), a processor linkable to the imagesensor and programmed to perform the steps of obtaining an image of theFOV and applying different decode algorithms to code candidates toattempt to decode the code candidates wherein the decode algorithmapplied to each candidate is a function of the location of the codecandidate in the FOV.

In some cases a first decode algorithm is applied to code candidateswithin a first region of interest (ROI) and a second decode algorithmthat is different than the first decode algorithm is applied to codecandidates in a second ROI that is different than the first ROI.

Other embodiments include an apparatus for decoding codes applied toobjects for use with an image sensor that includes a two dimensionalfield of view (FOV), the apparatus comprising an image sensor includinga two dimensional field of view (FOV), a processor linkable to the imagesensor and programmed to perform the steps of (i) obtaining image datacorresponding to an image of the FOV from the sensor, (ii) attempting todecode a the code candidate in the image using a first decode algorithm,(iii) where the attempt to decode the code candidate fails, maintainingthe image data in memory, (iv) repeating steps (i) through (iii) untilone of a threshold number of attempts to decode the code candidate havefailed and the code candidate has been successfully decoded, when thethreshold number of attempts to decode the code candidate have failed,accessing the image data maintained in memory and attempting to decodethe code candidate in at least a subset of the image data stored inmemory using a second decoding algorithm that is different than thefirst decoding algorithm.

To the accomplishment of the foregoing and related ends, the invention,then, comprises the features hereinafter fully described. The followingdescription and the annexed drawings set forth in detail certainillustrative aspects of the invention. However, these aspects areindicative of but a few of the various ways in which the principles ofthe invention can be employed. Other aspects, advantages and novelfeatures of the invention will become apparent from the followingdetailed description of the invention when considered in conjunctionwith the drawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a schematic diagram illustrating a hand-held code readerhaving features that are consistent with at least some aspects of thepresent invention;

FIG. 2 is a schematic diagram illustrating internal components includedin the hand-held device shown in FIG. 1;

FIG. 3 is an illustration of an exemplary field of view, exemplaryregions of interest within the field of view and exemplary codecandidates within the field of view;

FIG. 4 is similar to FIG. 3, albeit showing the code candidates indifferent relative positions with respect to the field of view and theregions of interest;

FIG. 5 is a flow chart illustrating a method whereby the processor shownin FIG. 2 performs different decode algorithms for code candidates indifferent regions of interest in a field of view;

FIG. 6 is a schematic diagram similar to FIG. 3, albeit showing adifferent region of interest pattern;

FIG. 7 is similar to FIG. 3, albeit showing another region of interestpattern;

FIG. 8 is similar to FIG. 3, albeit showing another region of interestpattern;

FIG. 9 is similar to FIG. 3, albeit showing a point of interest within afield of view as well as code candidates;

FIG. 10 is similar to FIG. 9, albeit showing a line of interest within afield of view;

FIG. 11 is a subprocess that may be substituted for a portion of theprocess shown in FIG. 5 whereby the region of interest pattern within afield of view is changed to optimize a decode process;

FIG. 12 is a process that may be performed by the processor shown inFIG. 2 for optimizing a decode process;

FIG. 13 is another process that may be performed by the processor ofFIG. 2 to optimize decode processes;

FIG. 14 is a process that may be performed by the processor of FIG. 2whereby a series of consecutive images are first examined in an attemptto decode code candidates using a simple decode algorithm after whichthe series of images may be reexamined in an attempt to decodecandidates using a relatively more complex decode algorithm; and

FIG. 15 is a flow chart illustrating a subprocess that may besubstituted for a portion of the process shown in FIG. 14 wherebysuccess factors are assigned to images and are used subsequently toidentify a subset of the images or an image order to be used during asubsequent decode processes.

While the invention is susceptible to various modifications andalternative forms, specific embodiments thereof have been shown by wayof example in the drawings and are herein described in detail. It shouldbe understood, however, that the description herein of specificembodiments is not intended to limit the invention to the particularforms disclosed, but on the contrary, the intention is to cover allmodifications, equivalents, and alternatives falling within the spiritand scope of the invention as defined by the appended claims.

DETAILED DESCRIPTION OF THE INVENTION

The various aspects of the subject invention are now described withreference to the annexed drawings, wherein like reference numeralscorrespond to similar elements throughout the several views. It shouldbe understood, however, that the drawings and detailed descriptionhereafter relating thereto are not intended to limit the claimed subjectmatter to the particular form disclosed. Rather, the intention is tocover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the claimed subject matter.

As used herein, the terms “component,” “system” and the like areintended to refer to a computer-related entity, either hardware, acombination of hardware and software, software, or software inexecution. For example, a component may be, but is not limited to being,a process running on a processor, a processor, an object, an executable,a thread of execution, a program, and/or a computer. By way ofillustration, both an application running on a computer and the computercan be a component. One or more components may reside within a processand/or thread of execution and a component may be localized on onecomputer and/or distributed between two or more computers or processors.

The word “exemplary” is used herein to mean serving as an example,instance, or illustration. Any aspect or design described herein as“exemplary” is not necessarily to be construed as preferred oradvantageous over other aspects or designs.

Furthermore, the disclosed subject matter may be implemented as asystem, method, apparatus, or article of manufacture using standardprogramming and/or engineering techniques to produce software, firmware,hardware, or any combination thereof to control a computer or processorbased device to implement aspects detailed herein. The term “article ofmanufacture” (or alternatively, “computer program product”) as usedherein is intended to encompass a computer program accessible from anycomputer-readable device, carrier, or media. For example, computerreadable media can include but are not limited to magnetic storagedevices (e.g., hard disk, floppy disk, magnetic strips . . . ), opticaldisks (e.g., compact disk (CD), digital versatile disk (DVD) . . . ),smart cards, and flash memory devices (e.g., card, stick). Additionallyit should be appreciated that a carrier wave can be employed to carrycomputer-readable electronic data such as those used in transmitting andreceiving electronic mail or in accessing a network such as the Internetor a local area network (LAN). Of course, those skilled in the art willrecognize many modifications may be made to this configuration withoutdeparting from the scope or spirit of the claimed subject matter.

Referring now to the drawings wherein like reference numerals correspondto similar elements throughout the several views and, more specifically,referring to FIGS. 1 and 2, the present invention will be described inthe context of an exemplary handheld symbol or code reader 10 includinga housing 101 having a grip section 102, a body/barrel section 104 and atrigger 111, a CCD or other type camera/sensor 105, optics/lenses 106, aprocessor 108, a timer 109, one or more indicator LEDs 132, LEDs (notillustrated) for illumination of a reader field of view, a speaker/audiocomponent 134, a battery 53, a memory 52 and a light source/subassembly54. Each of the processor 108, timer 109, battery 53, optics 106, memory52 and light source 54 are mounted in or otherwise supported by housing101. Processor 108 is linked to each of timer 109, battery 53, memory52, optics 106, camera/sensor 105, source 54, indicator LEDs 132, theillumination LEDs and output 134. Processor 108 runs programs stored inmemory 52 to perform inventive processes.

Unless indicated otherwise, the present invention will be described inthe context of the illustrated hand held reader device 10 and it will beassumed that the processor 108 is programmed to examine obtained imagesfor code candidates and to attempt to decode the code candidates untilany one of the candidates is successfully decoded. Once a candidate issuccessfully decoded, processor 108 causes LED 132 and/or output 134 togenerate a signal to indicate a successful decode to a device user.Nevertheless, it should be appreciated that at least some of the aspectsand embodiments herein would be applicable in reader devices mounted forstationary use or in cases where a processor is programmed to search forand decode more than one code in any image or set of images.

Referring again to FIGS. 1 and 2, optics 106 focus a field of view (FOV)107 on a CCD or other type of sensor device 105 within reader 10 whichin turn generates data comprising a high resolution images of itemslocated within FOV 107. Field of view 107 is centered along a FOV axis109. Thus, when the FOV 107 is directed toward a code 112 applied on asurface 128 of an item 130 and reader 10 is activated to generateimages, images including code 112 are obtained. Camera 105 generates arapid succession of consecutive images. While the time betweenconsecutive images is rapid, the time varies based on several factorsknown to those of skill in the code reading arts.

Referring now to FIG. 3, an exemplary FOV 107 is illustrated. Within theFOV 107, as shown, there are three code candidates 112 a, 112 b and 112c wherein only code candidate 112 b corresponds to an actual matrixcode. Thus, candidates 112 a and 112 c simply represent image artifactsthat, upon an initial analysis of the image, have some characteristicsthat are consistent with the artifacts being actual matrix codes to bedecoded.

Referring still to FIG. 3, in at least some embodiments of the presentinvention, the FOV 107 may be divided into separate regions of interest(ROIs) where different decode algorithms will be employed by processor108 (see again FIG. 2) to attempt to decode code candidates in thedifferent ROIs. For instance, in FIG. 3, an exemplary ROI 150 includes acircular central portion of the FOV 107. In this case, the balance ofthe FOV 107 outside the first ROI 150 may be considered a second ROI212. In this embodiment, it is contemplated that a first decodealgorithm is used to attempt to decode any code candidates within thefirst ROI 150 while a second decode algorithm is used to decode any codecandidates that exist in the second ROI 210. Thus, in FIG. 3, the firstdecode algorithm would be used to attempt to decode candidate 112 awhile the second decode algorithm would be used to attempt to decodecode candidate 112 c.

In at least some embodiments, the decode algorithm used to attempt todecode code candidate 112 b which is partially within the first ROI 150and partially within the second ROI 210 may depend upon the percentageof code candidate 112 b which resides within ROI 150. For instance,where more than 50% of candidate 112 b resided within ROI 150, the firstdecode algorithm may be used to attempt to decode candidate 112 b. Inother embodiment, if any part of a candidate such as 112 b resideswithin ROI 150, the first decode algorithm may be used to attempt todecode the candidate 112 b.

In the above example, in at least some embodiments, the first decodealgorithm used to attempt to decode code candidates within or associatedwith first ROI 150 will a relatively more robust or complex algorithmthat is relatively more computationally intensive than the second decodealgorithm and that therefore requires a greater amount of time tocomplete than the second decode algorithm. Herein, based on requiredtime, the first decode algorithm is said to be more expensive than theinexpensive second decode algorithm. Thus, for example, the first decodealgorithm may, on average, require a period three or more times greaterthan the period required to complete the second decode algorithm.

The example described above with respect to FIG. 3 where the first ROI150 includes a central portion of the field of view 107 is particularlyadvantageous in the context of a hand-held reader device 10 like the oneillustrated in FIG. 1 where a device user, aided by aiming illuminationfrom the device 10, moves the device 10 around in an attempt to alignFOV 107 with a code to be imaged and decoded. Thus, it has beenrecognized that a hand-held device user attempting to align a FOV with acode to be imaged will typically move the device around to increase FOVand code alignment until a code has been imaged and successfullydecoded. Thus, while a code to be imaged may initially reside withinsecond ROI 210 when images are first obtained, within a short time, thecode to be decoded will typically be located within first ROI 150 of FOV107. For instance, referring again to FIG. 3, the actual code 112 b tobe decoded is primarily located within the peripheral ROI 210 as shown.FIG. 4 shows an image similar to FIG. 3, albeit a short time thereafterwhen the hand-held device 10 (see again FIG. 1) has been moved by a userto better align the FOV 107 with candidate 112 b so that candidate 112 bresides within ROI 150.

Referring now to FIG. 5, an exemplary process 170 that may be performedby the processor 108 in FIG. 2 and that is consistent with the exampledescribed above with respect to FIGS. 3 and 4 is illustrated. At block171, regions of interest are defined and stored in memory 52 shown inFIG. 2. Referring again to FIG. 3, the exemplary ROIs that are definedand stored include ROIs 150 and 210 in the illustrated example. Next, atblock 172, camera sensor 105 in FIG. 2 obtains an image of the field ofview 107 and provides that image to processor 108. Upon receiving theimage, processor 108 identifies code candidates in the image at block174. Again, in FIG. 3, exemplary candidates that would be identifiedinclude candidate 112 a, 112 b, and 112 c. At block 176, processor 108identifies ROIs 150 and 210 in the image.

Continuing, at block 178 in FIG. 5, processor 108 attempts to decodecode candidates in the first ROI 150 using the first more expensive orcomplicated decode algorithm. Referring again to FIG. 3, at block 178processor 108 only attempts to decode code candidate 112 a using theexpensive algorithm as the other candidates 112 b and 112 c resideoutside ROI 150. At block 180, processor 108 attempts to decode codecandidates that reside in the second ROI 210 (e.g., within the portionof field of view outside first ROI 150) using a second or less expensivedecode algorithm. Thus, at block 180, processor 108 attempts to decodecode candidate 112 b and candidate 112 c using the second, lessexpensive decode algorithm. After block 180, control passes back up toblock 172 where camera 105 obtains a next image of the field of view 107and provides that image to processor 108.

The process shown in FIG. 5 continues repeatedly until any one of thecode candidates is successfully decoded. Thus, for instance, ifcandidate 112 b is successfully decoded using the second less expensivedecode algorithm, processor 108 indicates that the code has beensuccessfully decoded by illuminating LED 132 and/or generating a soundvia audio output 134 (see again FIG. 2) and the image obtaining andcandidate decoding process halts. In the example illustrated in FIGS. 3and 4, eventually, either the second decode algorithm will be successfulin decoding candidate 112 b or candidate 112 b will appear within thefirst ROI 150 and the first more expensive decode algorithm will beperformed by processor 108 to decode the candidate. While FIG. 5 showsthe first decode algorithm being performed first, in other embodimentsthe second decode algorithm may be performed for candidates in thesecond ROI first, followed by the first algorithm for candidates in thefirst ROI. In still other embodiments the first and second decodealgorithms may be commenced in parallel or performed at least in part inparallel as opposed to sequentially.

While FIG. 3 shows a circular central first ROI 150, it should beappreciated that the FOV 107 may be divided into many other ROIpatterns. For example, in at least some embodiments as shown in FIG. 3,the second ROI 210 may be divided into second and third ROIs 212 and210, respectively, where the second ROI 212 includes a portion of thefield of view 107 that surrounds the first ROI 150 and the third ROI 210includes the portion of the field of view 107 that surrounds the secondROI 212. Here, it is contemplated that processor 108 may be programmedto perform first, second and third different decode algorithms on codecandidates that appear within the first, second and third ROIs 15, 212and 210, respectively, in a fashion similar to that described above.

As another example, referring to FIG. 6, FOV 107 is shown divided intofirst and second ROIs 220 and 222, respectively, where the first ROI 220includes a central horizontal band through the field of view 107 and thesecond ROI 222 includes the balance of the field of view 107 above andbelow band 220. The embodiment shown in FIG. 6 may be particularlyuseful in the case of a reader device that is mounted for stationaryoperation above a transfer line where it is known that objects markedwith codes will typically be positioned on the transfer line such thatthe codes will usually appear within the band ROI 220.

Referring to FIG. 7, yet another ROI pattern is schematically shownwhere a first ROI 221 includes a rectangular portion of the FOV 107 andthe balance of the FOV 107 forms the second ROI 223. The ROI definitionshown in FIG. 7 maybe particularly useful where components (e.g., see219 in FIG. 7) are moved along by a transfer line through the FOV 107and the camera 105 is triggered to obtain images for decoding purposesby an object position sensor and where it is known that a code appearingon an exemplary object will typically be within the first ROI 221 whenthe trigger occurs.

FIG. 8 shows yet another ROI pattern or definition schematically where afirst ROI 241 includes a space about a central portion of the FOV 107that flares out to one side and the second ROI 242 includes the balanceof the FOV 107. This ROI pattern may also be useful in the context of astationary reader device where a transfer line moves objects through thefield of view 107 from right to left as shown in FIG. 8 such that theless expensive decode algorithm is attempted first followed by the moreexpensive decode algorithm for each candidate and where the ROIs reflectthe fact that codes may typically appear within a central horizontalband of the FOV 107 in a specific application.

In some embodiments it is contemplated that ROIs may instead be definedby the distances from one or more points within the FOV 107. To thisend, referring now to FIG. 9, an exemplary central point or centralpoint of interest within the FOV 107 is identified by numeral 240. Here,each of the code candidates 112 a, 112 b and 112 c is located within anobtained image of the field of view 107 at a different distance frompoint 240. The first ROI may be defined by point 240 and a radial valueR1 from the point 240 such that any candidate within the distance R1from point 240 would be within the first ROI and therefore would bedecoded using the first, more expensive decode algorithm whilecandidates outside that space would be in the second ROI and decodedusing the second decode algorithm.

In still other embodiments, it is contemplated that, based on a known orestimated time for obtaining a next image, the processor 108 may beprogrammed to attempt to decode only a specific number of codecandidates using the first and relatively expensive decode algorithmwhere the candidates would be selected based on their locations and,more specifically, based on the distances between a point (e.g., see 240in FIG. 9) within the field of view and each of the candidates. Forexample, processor 108 may be programmed to attempt to decode only thethree code candidates which are closest to point 240 in FIG. 9 using thefirst decode algorithm and to attempt to decode any other codecandidates in the field of view 107 using the second decode algorithm.

Referring to FIG. 10, instead of identifying code candidate locationsbased on distance from a point, the locations may be based on distancefrom a line 250. Here, processor 108 would decode candidates closest tothe line 250 first and work outward to other candidates. Other geometricshapes in addition to a point or line for referencing candidatelocations are contemplated.

Referring once again to FIG. 3, while the example described above withrespect to FIG. 3 and the other examples described above require thatthe second decode algorithm be performed only on code candidates thatreside within a second ROI which is completely separate from the firstROI, in at least some embodiments, the second ROI may include the entireFOV 107 such that the second and the less expensive decode algorithm isperformed for every code candidate within the field of view 107. Thus,for instance, in FIG. 3, in at least some embodiments the second decodealgorithm would initially be performed on each of the code candidates112 a, 1112 b and 112 c. If the second decode algorithm successfullydecodes a code, processor 108 may indicate successful decoding and stopthe process. However, where the second decode algorithm is notsuccessful in decoding a code, the first decode algorithm would then beapplied to any code candidates within the first ROI. In still otherembodiments the first decode algorithm may in fact include the seconddecode algorithm so that the second algorithm is effectively performedfor all candidates in an image.

In still other embodiments ROIs may be selected essentially in real timeto reflect how a reader device user is using the device. For instance,an expensive ROI may be selected as a region of a FOV in which a codewas most recently successfully decoded during a prior decoding processor a current expensive ROI may be altered as a function of the locationof in which a code was most recently successfully decoded during a priordecoding process. For instance, referring again to FIG. 3, if candidatesare routinely decoded near the left edge of FOV 107 using an inexpensivedecode algorithm, that may be evidence that a user of a hand held deviceroutinely moves the device from the left while aligning with a code.Here, it may make sense to change the expensive ROI from the central ROI150 shown in FIG. 3 to the ROI 241 shown in FIG. 8.

In addition, in at least some embodiments it is contemplated that theROIs may be dynamically adjusted in order to optimize the decodingprocess as a function of reader operation. For example, in at least somecases it maybe that the circumstances surrounding image acquisitionresult in very good images which can be decoded relatively quickly usingeven the complex or expensive first decode algorithm such that the firstROI (e.g., see 150 in FIG. 3) size could be increased while stillattempting to decode all candidates within the first ROI using the firstdecode algorithm prior to the camera 105 generating a next image.

Referring now to FIG. 11, a subprocess 190 that may be substituted for aportion of the process shown in FIG. 5 is illustrated where a first ROIsize is adjusted to optimize the decoding process. To this end, afterROIs are identified at block 176 in FIG. 5, control may pass to block198 in FIG. 11 where processor 108 attempts to decode code candidates ina second ROI using a second decode algorithm. At block 200, processor108 attempts to decode code candidates in a first ROI using an firstrelatively expensive decode algorithm. At block 202, processor 108determines whether or not the processor has attempted to decode all ofthe candidates in the first ROI using the first decode algorithm. Whereadditional code candidates exist, control passes to block 204 whereprocessor 108 determines whether or not camera 105 has provided a nextimage. Where camera 105 has not provided a next image, control passesback up to block 200 where the process described above is repeated.

Referring still to FIG. 11, at block 204, when a next image has beenobtained from camera 105, control passes to block 207 where the size ofthe first ROI is decreased after which control passes back up to block174 in FIG. 5. Referring again to block 202, when processor 108determines that the processor has attempted to decode all of the codecandidates in the first ROI using the first decode algorithm, controlpasses to block 203. At decision block 203, processor determines whetheror not a next image has been received from camera 105. Where a nextimage has not been received from camera 105, control passes to block 206where processor 108 increase the size of the first ROI after whichcontrol passes to block 174 in FIG. 5. At block 203, if the processor108 determines that a next image has been obtained, control simplypasses to block 174 in FIG. 5 without adjusting the size of the firstROI.

Although not shown, in some cases, if processor 108 determines that anext image has not been obtained at block 203, processor 108 maydetermine a minimum time prior to obtaining a next image and onlyincrease the size of the first ROI if the minimum time is greater thansome threshold value. In addition, in at least some cases processor 108may be programmed to require a consecutive series (e.g., 5, 10, etc.) ofnegative results at block 203 for a series of images prior to increasingthe size of the first ROI at block 206.

In at least some embodiments it is contemplated that processor 108 mayonly perform a first relatively slow and expensive decode algorithm butthat the processor will only perform the decode algorithm on a subset ofthe code candidates within a field of view where the subset is based onlocation within the field of view. For example, referring again to FIG.9, processor 108 may be programmed to decode code candidates in an orderthat depends on the distances of the code candidates from center point240 of FOV 107 where the processor stops decoding candidates after anext image has been obtained and restarts the process using the nextimage. Thus, for instance, in FIG. 9, processor 108 would start withattempting to decode candidate 112 a which is closest to point 240.Next, if time permits, processor 108 would attempt to decode the secondclosest code candidate, candidate 112 b, using the first decodealgorithm which, if time permits, would be followed by an attempt todecode candidate 112 c using the first decode algorithm, and so on.

Referring to FIG. 12, a process 300 that maybe performed by processor108 to decode code candidates in an order that depends on their relativelocation with respect to a center point is shown. At block 302, an imageof the field of view is obtained. At block 204, code candidates withinthe images are identified. At block 310, processor 108 attempts todecode code candidates in the obtained image using the first relativelyexpensive decode algorithm starting at a point of interest (e.g., thecenter point 240 shown in FIG. 9) and working outward from there. Atblock 312, processor 108 determines whether or not a next image has beenobtained. If camera 105 has provided a next image at 312, control passesback up to block 304 where the process continues. At block 312, if anext image has not been obtained, control passes to block 314 whereprocessor 108 determines whether or not the processor has attempted todecode each of the code candidates within the field of view. When theprocessor 108 has not attempted to decode at least one of the codecandidates within the field of view, control passes back up to block 310where the process continues as illustrated. If the processor hasattempted to decode all the code candidates using the first decodealgorithm at block 314, control passes back up to block 302 where theprocessor 108 waits to receive the next image from the camera 105.

In at least some embodiments it is contemplated that camera 105 willprovide images substantially at regular intervals (e.g., within a knownperiod range) so that the period between images is generally known. Inthis case, processor 108 can be programmed to use timer 109 to timeoutthe period between consecutive images and to attempt to decode as manycode candidates as possible within the timeout periods where the subsetof candidates being decoded again would be based on location within thefield of view. For instance, referring again to FIG. 9, for example,processor 108 may be programmed to attempt to decode code candidates inan order wherein the processor attempts the candidate closest to centerpoint 240 first followed by the candidate second closest to point 240,and so on, until the imaging timeout period has transpired. Once thetimeout period has transpired, processor 108 would essentially discardthe code candidates that the processor has not yet attempted to decodeand instead would begin attempting to decode candidates in thesubsequent image.

Referring to FIG. 13, a process 320 whereby processor 108 uses animaging timeout timer to control the decode process is illustrated. Atblock 322, the processor 108 obtains an image of the field of view fromthe camera 105. At block 324, processor 108 starts timer 109 (see againFIG. 2). At block 326, processor 108 identifies code candidates in theimage. At block 328, processor 108 attempts to decode code candidates inthe image using the first relatively expensive and slow decode algorithmstarting at a point of interest (e.g., see point 240 in FIG. 9) andworking out.

At block 330, processor 108 determines whether or not the imagingtimeout period or threshold period has lapsed. Where the timeout periodhas not lapsed, control passes back up to block 328 where the processorcontinues to attempt to decode code candidates working outward from thepoint of interest. At block 330, once the imaging timeout period haslapsed, control passes back up to block 322 where processor 108 obtainsa next image from camera 105.

According to another aspect that is consistent with at least someembodiments of the present invention, in at least some cases processor108 may be programmed to attempt to decode code candidates withinobtained images using a simple and relatively rapid decode algorithmfirst and to store the consecutive images for subsequent processing if acode is not successfully decoded within one of the images. Thus, forinstance, processor 108 may be programmed to obtain a first image of afield of view, attempt to decode code candidates within the first imageusing a simple and rapid decode algorithm and to store the image forpossible subsequent processing when no code is successfully decodedwithin the image. Next, the processor 108 may be programmed to obtain asecond image of the field of view, perform the simple and rapid decodealgorithm on code candidates in the second image and, if at least onecode has not been successfully decoded in the second image, to store thesecond image for possible subsequent analysis. In at least oneembodiment this process may continue for five consecutive images whereeach image is stored if at least one code has not been successfullydecoded in the image. After the five images are stored, processor 108may be programmed to re-access at least a subset of the stored imagesand attempt to decode code candidates in the subset of images using arelatively more expensive decode algorithm.

Referring now to FIG. 14, a process 350 wherein processor 108 processesreceived images using a first decode algorithm and then subsequentlyprocesses those images using a second decode algorithm when decodeattempts have been unsuccessful is illustrated. At block 352, processor108 sets a counter F which represents the number of stored images tozero. At block 354, processor 108 obtains an image of the field of view.At block 356, processor 108 identifies code candidates in the image. Atblock 358, processor 108 attempts to decode code candidates in the imageusing a simple or relatively inexpensive decode algorithm.

At block 360 where the code candidates are not successfully decoded,control passes to block 368 where the image is stored in a persistentfashion (i.e., in a fashion that allows the image to be accessedsubsequently for possible additional processing). At block 370, theimage counter F is incremented by 1. At block 372, the image counter Fis compared to a threshold value (e.g., 5). Where the image countervalue F is not equal to the threshold value, control passes back up toblock 354 where another image is obtained and the process continues.Where the image counter value F is equal to the threshold value, controlpasses from decision block 372 to process block 374. At block 374, thestored images are accessed. At block 376, processor 108 attempts todecode the code candidates in the accessed images using a relativelycomplex decode algorithm which requires additional time. After block376, control passes to block 378.

Referring still to FIG. 14, at block 378, processor 108 determineswhether or not a code in any of the images has been successfullydecoded. Where a code has not been successfully decoded, control passesto block 366 where all of the images are cleared from memory after whichcontrol passes back up to block 352 where the image counter F is resetto zero. At block 378, where at least one code as been successfullydecoded, control passes to block 380 where processor 108 indicatessuccessful decoding via LED 132 and/or audio output 134. After block380, control passes to block 366 where the images from the memory arecleared after which control passes back up to block 352 where the imagecounter F is reset to zero.

Referring once again to FIG. 14, at block 360, where processor 108determine that a code has been successfully decoded, control passes toblock 362 where the processor 108 indicates successful decode via LED132 and/or audio output 134. After block 362, control passes to block366 where images are cleared from the memory after which control passesback up to block 352 where the image counter F is reset to zero.

In at least some embodiments it is contemplated that, when a simpledecode algorithm has been employed to attempt to decode candidates in animage and none of the decode attempts have been successful, a decodesuccess factor may be assigned to the image or to separate codecandidates within the image indicating how successful one or more of thedecode attempts was with respect to the image. Then, after decodeattempts corresponding to several images have been unsuccessful, whenthe images are re-accessed to attempt to decode using a more complex orexpensive decode algorithm, processor 108 may be programmed to eitherattempt to decode only code candidates or candidates in images that havehigh success factors or the order in which the images or candidates areexamined using the expensive decode algorithm may be a function of thesuccess factors. To this end, referring to FIG. 15, a subprocess 400that may be substituted fora portion of the process shown in FIG. 14 isillustrated. Referring also to FIG. 14, at block 360, when no decodeattempt has been successful for candidates in an image, control may passto block 402 in FIG. 15 where processor 108 identifies and stores adecode success factor for the image or separate success factors for eachof a subset of the candidates in the image. At block 404, processor 108stores the image in a persistent fashion and at block 406 processor 108increments the image counter F by 1.

Continuing, at block 408, processor 108 determines whether or not theimage counter F is equal to the threshold value. Where the image counterF is not equal to the threshold value, control passes back to block 354in FIG. 14.

Referring still to FIG. 15, at block 408, where the image counter F isequal to the threshold value, control passes to block 410 whereprocessor 108 accesses one or more of the stored images that have thebest decode success factor or factors or accesses the code candidates inthe images that have the best decode success factors. At block 412,processor 108 attempts to decode code candidates having the best decodesuccess factors or to decode code candidates in the accessed imagesusing the more complex decode algorithm. After block 412, control passesback up to block 378 in FIG. 14.

In still other embodiments, when images are re-accessed, code candidatesin one or a sub-set of images may be processed using an expensivealgorithm based on locations within the images. For instance, in somecases, processor 108 may only process candidates within and expensiveROI or within a threshold distance of a point, a line or some othergeometric shape or may only process a specific number of code candidatesclosest to a geometric shape using the expensive algorithm.

In at least some cases, while different decoding algorithms areperformed for different regions of interest, the different regions ofinterest may be completely separate regions that do not overlap or mayoverlap at least somewhat.

The particular embodiments disclosed above are illustrative only, as theinvention may be modified and practiced in different but equivalentmanners apparent to those skilled in the art having the benefit of theteachings herein. Furthermore, no limitations are intended to thedetails of construction or design herein shown, other than as describedin the claims below. It is therefore evident that the particularembodiments disclosed above may be altered or modified and all suchvariations are considered within the scope and spirit of the invention.Accordingly, the protection sought herein is as set forth in the claimsbelow.

As described above, in at least some embodiments the term “decode” isused to refer to a process of extracting salient features from codecandidates after those candidates have been identified and thenlogically decoding the extracted features by mathematically interpretingthe features to extract encoded data where the code candidates areidentified by some other process. In other embodiments it also makessense to use algorithms that have different relative expenses toidentify code candidates in an image where the algorithms selected toidentify code candidates are based on location or image ROI. Forinstance, referring again to FIG. 3, in some embodiments relativelyexpensive algorithms may be used to each of locate code candidates,extract features and logically decode in central ROI 150 while lessexpensive algorithms are used to perform the same functions in theperipheral region 210. Thus, each of the embodiments described above maybe modified by including the step of identifying code candidates in thedecode algorithm so that location dependent algorithms of differentexpenses are employed for the entire candidate identifying, extractingand logical decoding processes.

In addition, in at least some cases where decoding algorithms includethe candidate identifying process, it may be that the candidateidentifying processes have different relative expenses but that otherportions of the decoding algorithms are identical or substantiallysimilar. For instance, referring again to FIG. 3, the candidateidentifying portion of the decoding process may be relatively expensivefor central ROI 150 when compared to peripheral ROI 210, but theextracting and logical decoding portions of the algorithm may beidentical.

Thus, the invention is to cover all modifications, equivalents, andalternatives falling within the spirit and scope of the invention asdefined by the following appended claims.

To apprise the public of the scope of this invention, the followingclaims are made:

What is claimed is:
 1. A method for decoding codes applied to objects for use with an image sensor that includes a two dimensional field of view (FOV), the method comprising: obtaining, using the image sensor, an image, wherein the image includes a first region corresponding to a central portion of the image sensor FOV and a second region; attempting to decode a first code candidate in the first region of the image using a first decode algorithm; and attempting to decode a second code candidate in only the second region of the image using a second decode algorithm, wherein the first decode algorithm requires a greater amount of time to complete than the second decode algorithm.
 2. The method of claim 1, further comprising: attempting to identify one or more code candidates in the first region using a first identification algorithm; and attempting to identify one or more code candidates in the second region using a second identification algorithm, wherein the first identification algorithm requires a greater amount of time to complete than the second identification algorithm.
 3. The method of claim 2, wherein the attempt to identify one or more code candidates in the first region is executed in parallel with the attempt to identify one or more code candidates in the second region.
 4. The method of claim 1, further comprising: obtaining, using the image sensor, a second image, wherein the second image includes the second code candidate in the first region corresponding to the central portion of the image sensor FOV; attempting to decode the second code candidate in the first region of the second image using the first decode algorithm; and attempting to decode a third code candidate in the second region of the second image using the second decode algorithm.
 5. The method of claim 4, further comprising: determining that the first decode algorithm was applied to all code candidates in the first region prior to obtaining the second image; and in response to determining the first decode algorithm was applied to all code candidates in the first region prior to obtaining the second image, increasing the size of the size of the first region.
 6. The method of claim 4, further comprising: determining that the first decode algorithm was not applied to all code candidates in the first region prior to obtaining the second image; and in response to determining the first decode algorithm was not applied to all code candidates in the first region prior to obtaining the second image, decreasing the size of the size of the first region.
 7. The method of claim 1, wherein the first decode algorithm comprises a first identifying algorithm, and the second decode algorithm comprises a second identifying algorithm, wherein the first identification algorithm requires a greater amount of time to complete than the second identification algorithm.
 8. The method of claim 7, wherein the greater amount of time to complete the first decode algorithm corresponds to the greater amount of time to complete the first identification algorithm.
 9. The method of claim 1, wherein the attempt to decode the second code candidate is executed in parallel with the attempt to decode the first code candidate.
 10. A method of claim 1, for decoding codes applied to objects for use with an image sensor that includes a two dimensional field of view (FOV), the method comprising: obtaining, using the image sensor, an image, wherein the image includes a first region corresponding to a central portion of the image sensor FOV and a second region; attempting to decode a first code candidate in the first region of the image using a first decode algorithm; and attempting to decode a second code candidate in the second region of the image using a second decode algorithm, wherein the first decode algorithm requires a greater amount of time to complete than the second decode algorithm, and wherein the attempt to decode the second code candidate is executed in parallel with the attempt to decode the first code candidate.
 11. An apparatus for decoding codes applied to objects for use with an image sensor that includes a two dimensional field of view (FOV), the apparatus comprising: an image sensor including a two dimensional field of view (FOV); and a processor linkable to the image sensor and programmed to perform the steps of: obtaining, using the image sensor, an image, wherein the image includes a first region corresponding to a central portion of the image sensor FOV and a second region; attempting to decode a first code candidate in the first region of the image using a first decode algorithm; and attempting to decode a second code candidate in only the second region of the image using a second decode algorithm, wherein the first decode algorithm requires a greater amount of time to complete than the second decode algorithm.
 12. The apparatus of claim 11, wherein the processor is further programmed to perform the steps of: attempting to identify one or more code candidates in the first region using a first identification algorithm; and attempting to identify one or more code candidates in the second region using a second identification algorithm, wherein the first identification algorithm requires a greater amount of time to complete than the second identification algorithm.
 13. The apparatus of claim 12, wherein the attempt to identify one or more code candidates in the first region is executed in parallel with the attempt to identify one or more code candidates in the second region.
 14. The apparatus of claim 11, wherein the processor is further programmed to perform the steps of: obtaining, using the image sensor, a second image, wherein the second image includes the second code candidate in the first region corresponding to the central portion of the image sensor FOV; attempting to decode the second code candidate in the first region of the second image using the first decode algorithm; and attempting to decode a third code candidate in the second region of the second image using the second decode algorithm.
 15. The apparatus of claim 14, wherein the processor is further programmed to perform the steps of: determining that the first decode algorithm was applied to all code candidates in the first region prior to obtaining the second image; and in response to determining the first decode algorithm was applied to all code candidates in the first region prior to obtaining the second image, increasing the size of the size of the first region.
 16. The apparatus of claim 14, wherein the processor is further programmed to perform the steps of: determining that the first decode algorithm was not applied to all code candidates in the first region prior to obtaining the second image; and in response to determining the first decode algorithm was not applied to all code candidates in the first region prior to obtaining the second image, decreasing the size of the size of the first region.
 17. The apparatus of claim 11, wherein the first decode algorithm comprises a first identifying algorithm, and the second decode algorithm comprises a second identifying algorithm, wherein the first identification algorithm requires a greater amount of time to complete than the second identification algorithm.
 18. The apparatus of claim 17, wherein the greater amount of time to complete the first decode algorithm corresponds to the greater amount of time to complete the first identification algorithm.
 19. The apparatus of claim 11, wherein the attempt to decode the second code candidate is executed in parallel with the attempt to decode the first code candidate.
 20. An apparatus of claim 11, for decoding codes applied to objects for use with an image sensor that includes a two dimensional field of view (FOV), the apparatus comprising: an image sensor including a two dimensional field of view (FOV); and a processor linkable to the image sensor and programmed to perform the steps of: obtaining, using the image sensor, an image, wherein the image includes a first region corresponding to a central portion of the image sensor FOV and a second region; attempting to decode a first code candidate in the first region of the image using a first decode algorithm; and attempting to decode a second code candidate in the second region of the image using a second decode algorithm, wherein the first decode algorithm requires a greater amount of time to complete than the second decode algorithm, and wherein the attempt to decode the second code candidate is executed in parallel with the attempt to decode the first code candidate. 